Detection method of subgrade settlement for the road of ART in coastal tidal flat area based on Vehicle-mounted binocular stereo vision technology

To address the problem present in current subgrade settlement detection methods, this paper proposes a nondestructive intelligent and dynamic detection method for subgrade settlement based on vehicle-mounted binocular stereo vision technology. This method aims to achieve all season, the whole road, long-term detection of subgrade settlement for Road of ART (Autonomous rail Rapid Transit) in coastal tidal flat areas. Firstly, improved Schneider encoding is adopted as the marker for subgrade settlement monitoring points. Binocular camera calibration and stereo rectification are performed using Zhang's method and the Bouguet algorithm before acquiring the marker images at the monitoring points, followed by efficient capture of Schneider ring coding images by the vehicle-mounted binocular stereo vision system. Thirdly, OpenCV is employed to preprocess the images, which improve image quality, eliminate noise, and enhance the features of the ring coding markers. On this basis, an improved SGBM algorithm is utilized for binocular stereo matching. Finally, according to the principle of triangulation, the three-dimensional coordinates of the monitoring points are obtained, and the corresponding settlement values of each monitoring point are determined through decoding and matching. Experimental results indicate that, for a true settlement value of 60 mm, the proposed detection method achieves an average settlement value of 58.897 mm, with a relative error rate of 1.84%. In the same experimental environment, the relative error rate of using a monocular camera detection method is 10.3%. The vehicle-mounted binocular camera method, with lower relative error than the monocular camera, offers a more efficient and accurate solution for nondestructive subgrade settlement detection, enhancing its intelligence.